The traditional approach to stochastic volatility (SV) modelling begins with the specification of an SV process, typically on the grounds of its analytical tractability (see, for example, Heston, 1993 ...

Stochastic volatility models have revolutionised the field of option pricing by allowing the volatility of an asset to vary randomly over time rather than remain constant. These models have ...

A stochastic volatility model where volatility was driven solely by a latent variable called news was estimated for three stock indices. A Markov chain Monte Carlo algorithm was used for estimating ...

Peter Friz, Paolo Pigato and Jonathan Seibel propose a modification of a given stochastic volatility model ‘backbone’ capable of producing extreme short-dated implied skews, without adding jumps or ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

Spot prices in energy markets exhibit special features, such as price spikes, mean reversion, stochastic volatility, inverse leverage effect, and dependencies between the commodities. In this paper a ...

This article empirically compares the Markov-switching and stochastic volatility diffusion models of the short rate. The evidence supports the Markov-switching diffusion model. Estimates of the ...

Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those ...

Options are a financial instrument that give the holder the right to buy and sell an underlying asset, at a predetermined price, on or before a specified date. For example, European-style options ...